In order to fit the SMB models, [1]} used the R-INLA software [2]}, which employs an approximate Bayesian inference scheme based on nested Laplace approximations for computing approximate posterior distributions over relevant quantities. Additionally, this software implements the scheme of [3]} in order to approximate the solution to the SPDE in (REF ) as a linear combination of basis functions that are derived from a finite element method (FEM). The FEM leads to the use of sparse precision matrices, with which computations can be done efficiently using sparse matrix algebra routines; see, for example, [4]}.
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